Exploring risk factors for long-term sickness absence during emerging adulthood: Continuous and discrete time models using Young-HUNT data on psychological distress and chronic pain.

Abstract

Long-term sickness absence (LTSA) in young adults has important consequences for labour market participation and future work disability. Chronic pain and psychological distress are key risk factors and frequently co-occur, yet their combined impact during adolescence on later LTSA remains insufficiently understood. This study aims to explore factors that influence adolescents' and young people's risk of receiving LTSA benefits during emerging adulthood. This longitudinal study used data from the Young-HUNT1 (1995-1997; n = 8736) and Young-HUNT3 (2006-2008; n = 7935) cohorts linked to Norwegian registry data and followed into early adulthood. The outcome was time to LTSA (≥90 or ≥180 days). Associations were examined using Cox proportional hazards models and Kaplan-Meier analyses. Continuous- and discrete-time models were developed and evaluated using the concordance index, time-dependent AUC, and integrated Brier score. Risk factors were analysed using SurvSHAP, SHAP, and regression-based methods. Chronic pain and co-occurring pain and psychological distress were consistently associated with increased LTSA risk (adjusted HRs between 1.3 and 1.5 for pain and between 1.6 and 1.7 for co-occurrence). In contrast, psychological distress alone showed no consistent association. Model performance was moderate and similar across approaches (C-index between 0.63 and 0.67). Key predictors included female sex, low parental education, chronic pain, poor perceived health, and indicators of early health problems. Adolescent chronic pain, particularly when co-occurring with psychological distress, is an important predictor of LTSA in early adulthood. While absolute LTSA levels may vary across cohorts, underlying risk patterns remain stable. More complex models did not outperform traditional approaches. These findings highlight the importance of early-life conditions and support early identification and intervention to reduce later work absence.